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Ling Pan

潘玲
Assistant Professor
Department of Electronic and Computer Engineering
Department of Computer Science and Engineering (by courtesy)
Hong Kong University of Science and Technology
Email: lingpan [@] ust [DOT] hk


Ling Pan is a Tenure-Track Assistant Professor in the Department of Electronic and Computer Engineering and the Department of Computer Science and Engineering (by courtesy) at the Hong Kong University of Science and Technology (HKUST) from Spring 2024. Her research focuses on theoretical understanding, algorithmic improvements, and practical application of (reward-maximizing) deep reinforcement learning, (reward-matching) GFlowNets, and multi-agent systems, aiming to develop robust, efficient, and practical intelligent decision-making algorithms. She is also interested in the application of decision-making algorithms in practical problems including scientific discovery, computational sustainability, and the alignment of foundation models. Before joining HKUST, she was a postdoctoral fellow at Mila supervised by Prof. Yoshua Bengio (Turing Award Laureate). She obtained her Ph.D. from the Institute for Interdisciplinary Information Sciences (IIIS) (headed by Prof. Andrew Yao), Tsinghua University in 2022, during which she visited Stanford University advised by Prof. Tengyu Ma, University of Oxford advised by Prof. Shimon Whiteson. She received her B.E. from the School of Computer Science and Engineering, Sun Yat-Sen (Zhongshan) University in 2017. Her work has been recognized by the AAAI New Faculty Highlights program, and she was awarded the Microsoft Research PhD Fellowship (Asia).

Please drop me an email if you are interested in collaborating with me.

Prospective Students: I am actively looking for self-motivated students (including undergraduate/graduate students and research assistants) who are interested in the areas of artificial intelligence and machine learning. I have several PhD/MPhil/RA openings starting in Spring 2026/Fall 2026 at HKUST. Please drop me an email with your CV (including rankings/publications) if you are interested.

Selected Awards

  • AAAI New Faculty Highlights, 2025
  • Outstanding Doctoral Thesis, by Tsinghua University, 2022
    Thesis: Towards Robust, Efficient, and Practical Deep Reinforcement Learning Algorithms
    The only selected computer science doctoral thesis in IIIS, Tsinghua University
  • Outstanding Graduate (top 3%), by Tsinghua University, 2022
    Also Beijing outstanding graduate and IIIS, Tsinghua University outstanding graduate, 2022
  • Microsoft Research Ph.D. Fellowship (Asia), 2020
  • China National Scholarship (top 2%), by Ministry of Education of China, 2014/2015/2016/2021

Professional Activities

  • Organizer:
  • Area Chair:
    • Conference on Neural Information Processing Systems (NeurIPS)
    • International Conference on Autonomous Agents and Multiagent Systems (AAMAS)
    • Reinforcement Learning Conference (RLC)
  • PC member/Reviewer:
    • ICML/NeurIPS/ICLR/AAAI/TMLR/TPAMI

Selected Talks

  • Towards Robust, Efficient, and Practical Decision-Making: From Reward-Maximizing Deep Reinforcement Learning to Reward-Matching GFlowNets
    RLChina 2024 Conference, October, 2024
    RLChina 2023 Conference, November, 2023
  • Towards Robust, Efficient, and Practical Reinforcement Learning
    Computer Science and Artificial Intelligence Lab (CSAIL), MIT, December, 2021
    Berkeley Artificial Intelligence Research (BAIR), UC Berkeley, November, 2021

Selected Grants

  • MTR Research Funding Scheme, PI, 2024 (≈HK$1.5M)
  • CCF-Kuaishou Large Model Explorer Fund, PI, 2024 (Acceptance rate: 10.1%)
  • NSFC Young Scientists Fund, PI, 2024
  • Tencent Rhino-Bird Focused Research Program, PI, 2024

Teaching

  • Sprint 2026: ELEC3350 Principles of Machine Learning
  • Spring 2025: ELEC6910J Deep Reinforcement Learning
  • Fall 2025/Fall 2024: ELEC2600 Probability and Random Process in Engineering